import torch
import sys
sys.path.append('E:\AI\DL')
import CNN.NiN as nin

X = torch.randn(size=(1,1,224,224))
net = nin.nin()
for block in net:
    X = block(X)
    print(block.__class__.__name__,'output_shape:',X.shape)